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1. Accurate prediction of cis -regulatory modules reveals a prevalent regulatory genome of humans

   https://doi.org/10.1093/nargab/lqab052  

   Ni, Pengyu ; Su, Zhengchang ( April 2021 , NAR Genomics and Bioinformatics)

   null (Ed.)

   Abstract cis-regulatory modules(CRMs) formed by clusters of transcription factor (TF) binding sites (TFBSs) are as important as coding sequences in specifying phenotypes of humans. It is essential to categorize all CRMs and constituent TFBSs in the genome. In contrast to most existing methods that predict CRMs in specific cell types using epigenetic marks, we predict a largely cell type agonistic but more comprehensive map of CRMs and constituent TFBSs in the gnome by integrating all available TF ChIP-seq datasets. Our method is able to partition 77.47% of genome regions covered by available 6092 datasets into a CRM candidate (CRMC) set (56.84%) and a non-CRMC set (43.16%). Intriguingly, the predicted CRMCs are under strong evolutionary constraints, while the non-CRMCs are largely selectively neutral, strongly suggesting that the CRMCs are likely cis-regulatory, while the non-CRMCs are not. Our predicted CRMs are under stronger evolutionary constraints than three state-of-the-art predictions (GeneHancer, EnhancerAtlas and ENCODE phase 3) and substantially outperform them for recalling VISTA enhancers and non-coding ClinVar variants. We estimated that the human genome might encode about 1.47M CRMs and 68M TFBSs, comprising about 55% and 22% of the genome, respectively; for both of which, we predicted 80%. Therefore, the cis-regulatory genome appears to be more prevalent than originally thought. 

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2. Prevalent use and evolution of exonic regulatory sequences in the human genome

   https://doi.org/10.1002/ntls.20220058  

   Chen, Jing ; Ni, Pengyu ; Wu, Siwen ; Niu, Meng ; Guo, Jun‐tao ; Su, Zhengsheng ( March 2023 , Natural Sciences)

   It has long been known that exons can serve ascis‐regulatory sequences, such as enhancers. However, the prevalence of such dual‐use of exons and how they evolve remain elusive. Based on our recently predicted, highly accurate large sets ofcis‐regulatory module candidates (CRMCs) and non‐CRMCs in the human genome, we find that exonic transcription factor binding sites (TFBSs) occupy at least a third of the total exon lengths, and 96.7% of genes have exonic TFBSs. Both A/T and C/G in exonic TFBSs are more likely under evolutionary constraints than those in non‐CRMC exons. Exonic TFBSs in codons tend to encode loops rather than more critical helices and strands in protein structures, while exonic TFBSs in untranslated regions (UTRs) tend to avoid positions where known UTR‐related functions are located. Moreover, active exonic TFBSs tend to be in close physical proximity to distal promoters whose genes have elevated transcription levels. These results suggest that exonic TFBSs might be more prevalent than originally thought and likely in dual‐use. We proposed a parsimonious model that well explains the observed evolutionary behaviors of exonic TFBS as well as how a stretch of codons evolve into a TFBS.

   There are more exonic regulatory sequences in the human genome than originally thought.

   Exonic transcription factor binding sites are more likely under negative selection or positive selection than counterpart nonregulatory sequences.

   Exonic transcription factor binding sites tend to be located in genome sequences that encode less critical loops in protein structures, or in less critical parts in 5′ and 3′ untranslated regions.

    

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3. PCRMS: a database of predicted cis-regulatory modules and constituent transcription factor binding sites in genomes

   https://doi.org/10.1093/database/baac024  

   Ni, Pengyu ; Su, Zhengchang ( January 2022 , Database)

   Abstract More accurate and more complete predictions of cis-regulatory modules (CRMs) and constituent transcription factor (TF) binding sites (TFBSs) in genomes can facilitate characterizing functions of regulatory sequences. Here, we developed a database predicted cis-regulatory modules (PCRMS) (https://cci-bioinfo.uncc.edu) that stores highly accurate and unprecedentedly complete maps of predicted CRMs and TFBSs in the human and mouse genomes. The web interface allows the user to browse CRMs and TFBSs in an organism, find the closest CRMs to a gene, search CRMs around a gene and find all TFBSs of a TF. PCRMS can be a useful resource for the research community to characterize regulatory genomes. Database URL: https://cci-bioinfo.uncc.edu/ 

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4. Accurate prediction of functional states of cis-regulatory modules reveals common epigenetic rules in humans and mice

   https://doi.org/10.1186/s12915-022-01426-9  

   Ni, Pengyu ; Moe, Joshua ; Su, Zhengchang ( October 2022 , BMC Biology)

   Predicting cis-regulatory modules (CRMs) in a genome and their functional states in various cell/tissue types of the organism are two related challenging computational tasks. Most current methods attempt to simultaneously achieve both using data of multiple epigenetic marks in a cell/tissue type. Though conceptually attractive, they suffer high false discovery rates and limited applications. To fill the gaps, we proposed a two-step strategy to first predict a map of CRMs in the genome, and then predict functional states of all the CRMs in various cell/tissue types of the organism. We have recently developed an algorithm for the first step that was able to more accurately and completely predict CRMs in a genome than existing methods by integrating numerous transcription factor ChIP-seq datasets in the organism. Here, we presented machine-learning methods for the second step.

   We showed that functional states in a cell/tissue type of all the CRMs in the genome could be accurately predicted using data of only 1~4 epigenetic marks by a variety of machine-learning classifiers. Our predictions are substantially more accurate than the best achieved so far. Interestingly, a model trained on a cell/tissue type in humans can accurately predict functional states of CRMs in different cell/tissue types of humans as well as of mice, and vice versa. Therefore, epigenetic code that defines functional states of CRMs in various cell/tissue types is universal at least in humans and mice. Moreover, we found that from tens to hundreds of thousands of CRMs were active in a human and mouse cell/tissue type, and up to 99.98% of them were reutilized in different cell/tissue types, while as small as 0.02% of them were unique to a cell/tissue type that might define the cell/tissue type.

   Our two-step approach can accurately predict functional states in any cell/tissue type of all the CRMs in the genome using data of only 1~4 epigenetic marks. Our approach is also more cost-effective than existing methods that typically use data of more epigenetic marks. Our results suggest common epigenetic rules for defining functional states of CRMs in various cell/tissue types in humans and mice.

    

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5. Genetic effects of sequence-conserved enhancer-like elements on human complex traits

   https://doi.org/10.1186/s13059-023-03142-1  

   Zhu, Xiang ; Ma, Shining ; Wong, Wing Hung ( January 2024 , Genome Biology)

   The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits.

   Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes.

   Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.

    

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